Final Project

Step 1:Download packages

library(mosaic)
library(DataComputing)
library(tidyverse)
library(mosaicData)
library(dplyr)
library("rjson")

Step 2:Importing and preparing data

Canada <- read.csv("CAvideos.csv")
US <- read.csv("USvideos.csv")
GreatBritain <- read.csv(("GB.csv"))

Step 3:Look at the datatable by using summary functions

head(Canada)

tail(US)

names(GreatBritain)

 [1] "video_id"               "trending_date"          "title"                  "channel_title"         
 [5] "category_id"            "publish_time"           "tags"                   "views"                 
 [9] "likes"                  "dislikes"               "comment_count"          "thumbnail_link"        
[13] "comments_disabled"      "ratings_disabled"       "video_error_or_removed" "description"           
[17] "X"                      "X.1"                    "X.2"                    "X.3"                   
[21] "X.4"                    "X.5"                    "X.6"                    "X.7"                   
[25] "X.8"                    "X.9"                    "X.10"                   "X.11"                  
[29] "X.12"                   "X.13"                   "X.14"                   "X.15"                  
[33] "X.16"                   "X.17"                   "X.18"                   "X.19"                  
[37] "X.20"                   "X.21"                   "X.22"                   "X.23"                  
[41] "X.24"                   "X.25"                  

Step 4:Data Wrangling

GreatBritain <-
  GreatBritain %>%
  select(title,publish_time,channel_title,category_id,publish_time,tags,views,likes,dislikes,comment_count,thumbnail_link,description)

GreatBritain %>%
  filter(category_id == 10)